Exploratory data analysis with MATLAB. 2nd ed. One of the goals of our first book, Computational Statistics Handbook with MATLAB, was to show some of the key concepts and methods of computational statistics and how they can be implemented in MATLAB. A core component of computational statistics is the discipline known as exploratory data analysis or EDA. Thus, we see this book as a complement to the first one with similar goals: to make exploratory data analysis techniques available to a wide range of users. This text is not focused on the theoretical aspects of the methods. Rather, the main focus of this book is on the use of the EDA methods. Thus, we do not dwell so much on implementation and algorithmic details. Instead, we show students and practitioners how the methods can be used for exploratory data analysis by providing examples and applications.

References in zbMATH (referenced in 22 articles , 1 standard article )

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  1. Machado, J. Tenreiro; Luchko, Yuri: Multidimensional scaling and visualization of patterns in distribution of nontrivial zeros of the zeta-function (2021)
  2. Martinez, Wendy L.; Martinez, Angel R.; Solka, Jeffrey L.: Exploratory data analysis with MATLAB (2017)
  3. Bergomi, Mattia G.; Baratè, Adriano; Di Fabio, Barbara: Towards a topological fingerprint of music (2016)
  4. Hasnat, Md. Abul; Alata, Olivier; Trémeau, Alain: Model-based hierarchical clustering with Bregman divergences and fishers mixture model: application to depth image analysis (2016)
  5. Sizikov, Valery; Sidorov, Denis: Generalized quadrature for solving singular integral equations of Abel type in application to infrared tomography (2016)
  6. Tenreiro Machado, J. A.; Lopes, António M.: Fractional state space analysis of temperature time series (2015)
  7. Lopes, António M.; Tenreiro Machado, J. A.: Analysis of temperature time-series: embedding dynamics into the MDS method (2014)
  8. Tabor, J.; Spurek, P.: Cross-entropy clustering (2014)
  9. Alaei, Hesam Komari; Salahshoor, Karim; Alaei, Hamed Komari: A new integrated on-line fuzzy clustering and segmentation methodology with adaptive PCA approach for process monitoring and fault detection and diagnosis (2013) ioport
  10. Preoteasa, Cristina Teodora; Ionescu, Ecaterina; Preoteasa, Elena; Machado, J. A. Tenreiro; Baleanu, Mihaela Cristina; Baleanu, Dumitru: Multidimensional scaling for orthodontic root resorption (2013) ioport
  11. Lima, Miguel F. M.; Tenreiro Machado, J. A.; Costa, António C.: A multidimensional scaling analysis of musical sounds based on pseudo phase plane (2012)
  12. Tenreiro Machado, J.: Multidimensional scaling analysis of fractional systems (2012)
  13. Foresti, Loris; Tuia, Devis; Kanevski, Mikhail; Pozdnoukhov, Alexei: Learning wind fields with multiple kernels (2011)
  14. Martinez, Wendy L.; Martinez, Angel R.; Solka, Jeffrey L.: Exploratory data analysis with MATLAB (2011)
  15. Søe-Knudsen, Alf: Design of stop-band filter by use of curved pipe segments and shape optimization (2011)
  16. James, Alex Pappachen; Dimitrijev, Sima: Inter-image outliers and their application to image classification (2010)
  17. Szőke, Ákos: Bin-packing-based planning of agile releases (2010)
  18. Perrotta, Domenico; Riani, Marco; Torti, Francesca: New robust dynamic plots for regression mixture detection (2009)
  19. Palumbo, Francesco; Vistocco, Domenico; Morineau, Alain: Huge multidimensional data visualization: back to the virtue of principal coordinates and dendrograms in the new computer age (2008)
  20. Steinley, Douglas; Brusco, Michael J.: Selection of variables in cluster analysis: An empirical comparison of eight procedures (2008)

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